code: def simplify(
      input: Union[
          Operator, MeasurementProcess, QuantumTape, QNode, Callable
      ]
  ):
      """Simplifies an operator, tape, qnode or quantum function by reducing its arithmetic depth
      or number of rotation parameters.
  
      Args:
          input (.Operator, .MeasurementProcess, pennylane.QNode, .QuantumTape, or Callable): an
              operator, quantum node, tape or function that applies quantum operations
  
      Returns:
          (Operator or MeasurementProcess or qnode (QNode) or quantum function (Callable)
          or tuple[List[QuantumTape], function]): Simplified input. If an operator or measurement
          process is provided as input, the simplified input is returned directly. Otherwise, the
          transformed circuit is returned as described in :func:`qml.transform <pennylane.transform>`.
  
      **Example**
  
      Given an instantiated operator, ``qml.simplify`` reduces the operator's arithmetic depth:
  
      >>> op = qml.adjoint(qml.RX(0.54, wires=0) + qml.PauliX(0) + qml.PauliZ(1))
      >>> op.arithmetic_depth
      3
      >>> sim_op = qml.simplify(op)
      >>> sim_op.arithmetic_depth
      2
      >>> type(sim_op)
      pennylane.ops.op_math.sum.Sum
      >>> sim_op.operands
      (Adjoint(RX)(0.54, wires=[0]),
      Adjoint(PauliX)(wires=[0]),
      Adjoint(PauliZ)(wires=[1]))
  
      This function can also simplify the number of rotation gate parameters:
  
      >>> qml.simplify(qml.Rot(np.pi / 2, 0.1, -np.pi / 2, wires=0))
      RX(0.1, wires=[0])
  
      Both types of simplification occur together:
  
      >>> op = qml.adjoint(qml.U2(-np.pi/2, np.pi/2, wires=0) + qml.PauliX(0))
      >>> op
      Adjoint(Sum)([-1.5707963267948966, 1.5707963267948966], [], wires=[0])
      >>> qml.simplify(op)
      Adjoint(RX)(1.5707963267948966, wires=[0]) + Adjoint(PauliX)(wires=[0])
  
      Moreover, ``qml.simplify`` can be used to simplify QNodes or quantum functions:
  
      >>> dev = qml.device("default.qubit", wires=2)
      >>> @qml.qnode(dev)
      ... @qml.simplify
      ... def circuit():
      ...     qml.adjoint(qml.prod(qml.RX(1, 0) ** 1, qml.RY(1, 0), qml.RZ(1, 0)))
      ...     return qml.probs(wires=0)
      >>> circuit()
      tensor([0.64596329, 0.35403671], requires_grad=True)
      >>> list(circuit.tape)
      [RZ(11.566370614359172, wires=[0]) @ RY(11.566370614359172, wires=[0]) @ RX(11.566370614359172, wires=[0]),
       probs(wires=[0])]
      """
      if isinstance(input, (Operator, MeasurementProcess)):
          if QueuingManager.recording():
              with QueuingManager.stop_recording():
                  new_op = copy(input.simplify())
              QueuingManager.remove(input)
              return qml.apply(new_op)
          return input.simplify()
  
      if isinstance(input, QuantumScript) or callable(input):
          return _simplify_transform(input)
  
      raise ValueError(
          f"Cannot simplify the object {input} of type {type(input)}."
      )
  
file_path: pennylane/pennylane/ops/functions/simplify.py
imports: from copy import copy
  from typing import Callable, Union, Sequence
  import pennylane
  from pennylane.measurements import MeasurementProcess
  from pennylane.operation import Operator
  from pennylane.workflow import QNode
  from pennylane.queuing import QueuingManager
  from pennylane.tape import QuantumScript, QuantumTape
label_desc: Use image node_id 1 for calling a global function with example usage: simplify(input) and returns: input, _simplify_transform, qml